Associate Director, Applied Machine Learning at Best Buy in Richfield, Minnesota

Job Description:

We at Best Buy work hard every day to enrich the lives of customers through technology, whether they come to us online, visit our stores or invite us into their homes. We do this by solving technology problems and addressing key human needs across a range of areas, including entertainment, productivity, communicating with coworkers and loved ones, preparing nutritious food, providing security for your home and family, and helping you take your health to the next level.

As an Associate Director of Machine Learning Science – Planning & Optimization, you’ll have the opportunity to lead a team of machine learning scientists that are researching and developing cutting-edge machine learning and artificial intelligence algorithms that solve some of the company's hardest problems and transform the way Best Buy operates day-to-day. In this role you will combine strategic thinking with your leadership skills, strong software engineering expertise and deep knowledge of ML and AI algorithms to lead a team focused on architecting, developing, and operationalizing models, algorithms, and production quality codebases that power key capabilities including forecasting, labor planning, optimal inventory placement, supply chain optimization, improving the performance of advertising/marketing campaigns, and automating media campaign planning and management.

Join us if you want to spend your time:

• Leading a team of top-tier machine learning scientists as they build some of the most business critical capabilities that will accelerate Best Buy’s strategic growth


• Guiding development of highly scalable algorithms based on state-of-the-art machine learning techniques such as new applications of transformers/multi-headed self-attention, Bayesian/stochastic optimization, probabilistic graphical models, spatio-temporal graphs, and graph neural networks


• Applying software engineering/architecture knowledge to guide teams developing and deploying solutions that can scale to solving enormously complex billion node graph problems or serve millions of requests per second with millisecond latency


• Utilizing broad and deep knowledge of machine learning and software engineering to contribute to the roadmap of Best Buy’s core machine learning capabilities


• Providing technical leadership for multiple efforts building real products that influence and enhance the lives of millions of people and drive and deliver tens of millions of dollars in impact to Best Buy’s bottom line


• Coaching and mentoring other machine learning scientists to elevate talent across Best Buy

• Bachelor's degree in a highly quantitative field (e.g. Computer Science, Engineering, Physics, Math, Operations Research, etc) or equivalent experience


• Extensive machine learning and algorithmic background with expert level understanding of at least one of the following areas: supervised and unsupervised learning methods, reinforcement learning, deep learning, Bayesian inference, graphical modeling, or nonlinear/stochastic optimization


• 8 years of experience building ML and/or AI driven products or other similar related functions (e.g. software engineering, data science, advanced analytics). Advanced degrees in relevant fields may be counted towards experience requirements.


• 2 years of experience leading technical research and production grade development efforts/teams


• Excellent communication skills with a superb ability to communicate technical information to a wide spectrum of cross-functional team members


• Fluency with at least one data science/analytics programming language (e.g. Python, R, Julia)


• Strong software design and implementation skills with a general-purpose programming language (e.g. Scala, Swift, C++/C#, Java, Haskell, etc)

• 4+ years of experience with direct people management or leading technical teams


• Master's degree or Ph.D in a highly quantitative field (e.g. Computer Science, Engineering, Physics, Math, Operations Research, etc)


• Experience using high performance machine learning libraries and/or deep learning frameworks (e.g. PyTorch, Tensorflow, RAPIDs, etc)


• Experience building distributed data processing pipelines (e.g. Apache Spark, Apache Beam)


• Experience building scalable distributed products to implement batch, real-time, and streaming machine learning products


• Strong functional programming development skills